The Netflix TechBlog

MARCH 25, 2019

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can

Infrastructure 225

Infrastructure Big Data Transportation Architecture 225

Dynatrace

MARCH 11, 2021

In the fourth part of the series, I’ll show you how I used Dynatrace’s raw problem and event data to find the best fit for optimized anomaly detection settings. I took a big-data-analysis approach, which started with another problem visualization. Statistically analyzing Dynatrace’s event and problem data.

Tuning 264

Tuning Architecture Monitoring Big Data 264

The Netflix TechBlog

APRIL 29, 2019

Demand Engineering Demand Engineering is responsible for Regional Failovers , Traffic Distribution, Capacity Operations and Fleet Efficiency of the Netflix cloud. Orchestration The Big Data Orchestration team is responsible for providing all of the services and tooling to schedule and execute ETL and Adhoc pipelines.

Open Source 280

Open Source Network Infrastructure Big Data 280

Dynatrace

OCTOBER 17, 2022

Artificial intelligence for IT operations, or AIOps, combines big data and machine learning to provide actionable insight for IT teams to shape and automate their operational strategy. CloudOps includes processes such as incident management and event management. CloudOps: Applying AIOps to multicloud operations.

DevOps 246

DevOps Artificial Intelligence Healthcare Innovation 246

The Netflix TechBlog

OCTOBER 28, 2021

Netflix’s unique work culture and petabyte-scale data problems are what drew me to Netflix. During earlier years of my career, I primarily worked as a backend software engineer, designing and building the backend systems that enable big data analytics. What is your favorite project?

Data Engineering 181

Data Engineering Engineering Big Data Software Engineering 181

Dynatrace

MARCH 14, 2022

The healthcare industry is embracing cloud technology to improve the efficiency, quality, and security of patient care, and this year’s HIMSS Conference in Orlando, Fla., AIOps (or “AI for IT operations”) uses artificial intelligence so that big data can help IT teams work faster and more effectively.

Healthcare 246

Healthcare Artificial Intelligence Innovation Strategy 246

The Netflix TechBlog

JUNE 7, 2021

Flow Collector consumes two data streams, the IP address change events from Sonar via Kafka and eBPF flow log data from the Flow Exporter sidecars. It performs real time attribution of flow data with application metadata from Sonar. We use Sonar to attribute an IP address to a specific application at a particular time.

Network 327

Network Transportation AWS Cloud 327

Dynatrace

OCTOBER 14, 2021

Gartner defines AIOps as the combination of “big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination.” Typically, only the aggregated events will be accessible to ML and will often exclude additional details. What is AIOps?

Artificial Intelligence 246

Artificial Intelligence DevOps Innovation Metrics 246

Dynatrace

JUNE 1, 2020

With answers at your fingertips, data backed decisions, and real-time visibility into business KPIs, Dynatrace enables you to consistently deliver better digital business outcomes across all your channels more efficiently than ever before. Dynatrace APM – Named a Leader in APM and yet, we’re much more.

Artificial Intelligence 254

Artificial Intelligence Social Media Monitoring IoT 254

The Netflix TechBlog

JUNE 20, 2024

To handle errors efficiently, Netflix developed a rule-based classifier for error classification called “Pensive.” To address this, we propose developing an intelligent agent that can automatically discover, map, and query all data within an enterprise. Until next time!

Data Engineering 206

Data Engineering Engineering Entertainment Software Engineering 206

The Netflix TechBlog

DECEMBER 21, 2020

We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits. This article will list some of the use cases of AutoOptimize, discuss the design principles that help enhance efficiency, and present the high-level architecture.

Storage 212

Storage Latency Efficiency Data Engineering 212

Alex Podelko

DECEMBER 19, 2019

Boris has unique expertise in that area – especially in Big Data applications. Marrying Artificial Intelligence and Automation to Drive Operational Efficiencies by Priyanka Arora, Asha Somayajula, Subarna Gaine, Mastercard. How to select appropriate IT Infrastructure to support Digital Transformation by Boris Zibitsker, BEZNext.

Efficiency 100

Efficiency Artificial Intelligence Scalability Performance 100

Dynatrace

DECEMBER 15, 2022

Adding application security to development and operations workflows increases efficiency. AIOps (artificial intelligence for IT operations) combines big data, AI algorithms, and machine learning for actionable, real-time insights that help ITOps continuously improve operations. ITOps vs. AIOps.

Artificial Intelligence 246

Artificial Intelligence DevOps Hardware Virtualization 246

Dynatrace

JUNE 26, 2024

Automation Based on the sheer volume and variety of data available to observability tools, IT automation is critical to ensure efficient operations. While human oversight is required to ensure outputs meet expectations, relying on manual processes to collect and correlate data is no longer feasible. Predictive analysis.

Analytics 246

Analytics Infrastructure Metrics Efficiency 246

Dynatrace

MARCH 24, 2023

Container technology enables organizations to efficiently develop cloud-native applications or to modernize legacy applications to take advantage of cloud services. Apache Mesos with the Marathon DC/OS is popular for large-scale production clusters running existing workloads on big data systems, such as Hadoop, Kafka, and Spark.

Infrastructure 246

Infrastructure Open Source Operating System Cloud 246

Highly Scalable

MARCH 1, 2012

The idea is to keep all records for one user collocated, so it is possible to fetch such a frame into memory (one user can not produce too many events) and to eliminate site duplicates using hash table or whatever. An alternative technique is to have one entry for one user and append sites to this entry as events arrive.

Database 279

Database Ecommerce Efficiency Engineering 279

Highly Scalable

MAY 1, 2012

On the other hand, when one is interested only in simple additive metrics like total page views or average price of conversion, it is obvious that raw data can be efficiently summarized, for example, on a daily basis or using simple in-stream counters. what is the cardinality of the data set)? bits per unique value. Case Study.

Analytics 191

Analytics Traffic Big Data Efficiency 191

The Netflix TechBlog

NOVEMBER 20, 2023

We will show how we are building a clean and efficient incremental processing solution (IPS) by using Netflix Maestro and Apache Iceberg. IPS provides the incremental processing support with data accuracy, data freshness, and backfill for users and addresses many of the challenges in workflows. past 3 hours or 10 days).

Processing 219

Processing Big Data Efficiency Engineering 219

Dynatrace

FEBRUARY 16, 2023

As teams try to gain insight into this data deluge, they have to balance the need for speed, data fidelity, and scale with capacity constraints and cost. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022. But logs are just one pillar of the observability triumvirate.

Analytics 246

Analytics Innovation Metrics Database 246

The Netflix TechBlog

OCTOBER 18, 2022

by Jun He , Akash Dwivedi , Natallia Dzenisenka , Snehal Chennuru , Praneeth Yenugutala , Pawan Dixit At Netflix, Data and Machine Learning (ML) pipelines are widely used and have become central for the business, representing diverse use cases that go beyond recommendations, predictions and data transformations.

Java 211

Java Scalability Traffic Architecture 211

Scalegrid

JUNE 28, 2024

Key features of RabbitMQ include message persistence to prevent data loss, flexible routing capabilities, and support for multiple messaging protocols such as AMQP, MQTT, and STOMP, enhancing its adaptability and reliability. Businesses can maintain a reliable and efficient communication system by utilizing message queues.

IoT 130

IoT Healthcare Programming Open Source 130

All Things Distributed

DECEMBER 13, 2016

With the launch of the AWS Europe (London) Region, AWS can enable many more UK enterprise, public sector and startup customers to reduce IT costs, address data locality needs, and embark on rapid transformations in critical new areas, such as big data analysis and Internet of Things. Fraud.net is a good example of this.

AWS 155

AWS Cloud Artificial Intelligence IoT 155

Dynatrace

JUNE 1, 2020

With answers at your fingertips, data backed decisions, and real-time visibility into business KPIs, Dynatrace enables you to consistently deliver better digital business outcomes across all your channels more efficiently than ever before. Dynatrace APM – Named a Leader in APM and yet, we’re much more.

Monitoring 173

Monitoring Performance Social Media Artificial Intelligence 173

The Morning Paper

OCTOBER 26, 2020

On the surface this is a paper about fast data ingestion from high-volume streams, with indexing to support efficient querying. Helios also serves as a reference architecture for how Microsoft envisions its next generation of distributed big-data processing systems being built. PVLDB’20.

Cloud 104

Cloud Big Data Latency Architecture 104

The Netflix TechBlog

NOVEMBER 3, 2023

For more efficient schema management and evolution, the platform will automatically infer the output schema based on the fields selected by the SQL query. Once the user is done editing their query, it is saved to the Data Mesh Pipeline, which will then be deployed as a long running, streaming SQL job.

Processing 271

Processing Engineering Infrastructure Latency 271

Scalegrid

MARCH 28, 2024

Snapshots provide point-in-time captures of the dataset, which are efficient for recovery on startup. On the other hand, an append-only file ensures data safety by recording every write operation that modifies the dataset, allowing for complete data reconstruction in the event of a restart. Data transfer technology.

Cache 130

Cache Storage Scalability Architecture 130

High Scalability

MARCH 24, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 105

Education Software Engineering Engineering Big Data 105

High Scalability

APRIL 14, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 105

Education Software Engineering Scalability Engineering 105

ScaleOut Software

JULY 19, 2021

And it can maintain contextual information about every data source (like the medical history of a device wearer or the maintenance history of a refrigeration system) and keep it immediately at hand to enhance the analysis.

IoT 78

IoT Big Data Analytics Architecture 78

High Scalability

MAY 12, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 102

Education Software Engineering Scalability Engineering 102

High Scalability

APRIL 28, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 102

Education Software Engineering Scalability Engineering 102

High Scalability

MARCH 30, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 105

Education Software Engineering Engineering Big Data 105

The Morning Paper

MAY 14, 2019

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., For the services under study, Seer has a sweet spot when trained with around 100GB of data and a 100ms sampling interval for measuring queue depths. ASPLOS’19.

Big Data 45

Big Data Cloud Performance Hardware 45

High Scalability

MAY 26, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 100

Education AWS Software Engineering Scalability 100

Highly Scalable

MARCH 10, 2015

However, there are a number of other important applications: Manufacturer-sponsored discounts can fall into this category because a retailer is not concerned about the cost of the incentives (covered by the manufacturer), only about efficient targeting. A retailer offers a category of products to its customers. Stock level optimization.

Retail 152

Retail C++ Analytics Metrics 152

Abhishek Tiwari

DECEMBER 27, 2017

A unified data management (UDM) system combines the best of data warehouses, data lakes, and streaming without expensive and error-prone ETL. It offers reliability and performance of a data warehouse, real-time and low-latency characteristics of a streaming system, and scale and cost-efficiency of a data lake.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

Highly Scalable

JANUARY 31, 2012

It is worth noting that if MapReduce is used for sorting of the original (not intermediate) data, it is often a good idea to continuously maintain data in sorted state using BigTable concepts. In other words, it can be more efficient to sort data once during insertion than sort them for each MapReduce query.

C++ 144

C++ Network Ecommerce Processing 144